# Introduction In this lab, we will apply Non-negative Matrix Factorization (NMF) and Latent Dirichlet Allocation (LDA) on a corpus of documents to extract additive models of the topic structure of the corpus. The output will be a plot of topics, each represented as a bar plot using the top few words based on weights. ## VM Tips After the VM startup is done, click the top left corner to switch to the **Notebook** tab to access Jupyter Notebook for practice. Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook. If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.
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